WO2024256344A1 - Steuern eines haushaltsgeräts - Google Patents
Steuern eines haushaltsgeräts Download PDFInfo
- Publication number
- WO2024256344A1 WO2024256344A1 PCT/EP2024/065965 EP2024065965W WO2024256344A1 WO 2024256344 A1 WO2024256344 A1 WO 2024256344A1 EP 2024065965 W EP2024065965 W EP 2024065965W WO 2024256344 A1 WO2024256344 A1 WO 2024256344A1
- Authority
- WO
- WIPO (PCT)
- Prior art keywords
- household appliance
- language model
- response
- support request
- representation
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Ceased
Links
Classifications
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/22—Procedures used during a speech recognition process, e.g. man-machine dialogue
-
- G—PHYSICS
- G06—COMPUTING OR CALCULATING; COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F3/00—Input arrangements for transferring data to be processed into a form capable of being handled by the computer; Output arrangements for transferring data from processing unit to output unit, e.g. interface arrangements
- G06F3/16—Sound input; Sound output
- G06F3/167—Audio in a user interface, e.g. using voice commands for navigating, audio feedback
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/06—Creation of reference templates; Training of speech recognition systems, e.g. adaptation to the characteristics of the speaker's voice
- G10L15/063—Training
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/28—Constructional details of speech recognition systems
- G10L15/30—Distributed recognition, e.g. in client-server systems, for mobile phones or network applications
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L15/00—Speech recognition
- G10L15/08—Speech classification or search
- G10L2015/088—Word spotting
-
- G—PHYSICS
- G10—MUSICAL INSTRUMENTS; ACOUSTICS
- G10L—SPEECH ANALYSIS TECHNIQUES OR SPEECH SYNTHESIS; SPEECH RECOGNITION; SPEECH OR VOICE PROCESSING TECHNIQUES; SPEECH OR AUDIO CODING OR DECODING
- G10L25/00—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00
- G10L25/27—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the analysis technique
- G10L25/30—Speech or voice analysis techniques not restricted to a single one of groups G10L15/00 - G10L21/00 characterised by the analysis technique using neural networks
Definitions
- the present invention relates to the control of a household appliance.
- the invention relates to improved user guidance when controlling the household appliance.
- a household appliance such as a washing machine, includes controls that allow a user to select a predetermined program, set an option or obtain information about the appliance.
- user guidance is intuitive in most cases, there are cases where the user needs assistance. For example, the user may have a question about the correct use of an option or program, or the household appliance may signal an error or warning that is not self-explanatory.
- the user can consult a user manual that may be provided with the device.
- the user can contact a help center or a specialist.
- Another source of information includes a forum or documentation center that may be accessible via the Internet. These sources of information have in common that they are usually not trustworthy or do not address the user's specific problem or question. In addition, some methods require a longer wait time for an answer. Some sources are subject to payment. An answer is not always relevant or safe. In some cases, the user may follow advice and thereby make the problem worse or cause a new one.
- One object underlying the present invention is to provide an improved technology for controlling a household appliance.
- the invention solves this problem by means of the subject matter of the independent claims. Subclaims give preferred embodiments.
- a method for controlling a household appliance comprises steps of detecting a linguistically formulated support request in the area of the household appliance; converting the support request into a textual representation; determining a response in text form by means of a language model; converting the response into a linguistic representation; and outputting the linguistic representation on the household appliance.
- specialist knowledge and language understanding that can be achieved by means of a language model can be used to provide a specific response to a request formulated by a user of the household appliance.
- a linguistic interaction can take place between the household appliance and the user in order to solve an existing problem.
- the method can be controlled or triggered intuitively by the user.
- a response can be provided with little or no noticeable delay.
- the language model can be capable of learning so that increasingly better answers can be found over time based on the support requests of one or more users.
- the language model preferably comprises a large language model (LLM) implemented on an artificial neural network (ANN) with a large number of parameters.
- LLM large language model
- ANN artificial neural network
- ANN artificial neural network
- the language model can be operated by an external service provider and made available to respond to the support request.
- the quality of the responses provided can be improved by applying one or more measures for specific training or adaptation of the language model.
- the language model is trained on vocabulary related to the household appliance. For example, with regard to a washing machine, an improved technical understanding of a component such as a water pump, an eco-closure or an aqua stop can be achieved.
- the vocabulary can be incorporated into the language model so that the vocabulary can be put together to form sentences in a given context that are meaningful not only grammatically but also in terms of their meaning.
- the language model is trained to operate the household appliance.
- the contents of an instruction manual or a general user guide for household appliances of the same type or class can be used as training data.
- Other data sources can include, for example, a discussion in a forum or background information, such as from a scientific publication or a test report. For example, the user can find out about a washing machine how to gently remove a certain type of dirt from a given textile.
- the language model is trained with respect to a function of the household appliance. For example, information from a service manual or a general work regarding the function of the present class of household appliances can be used as training data.
- the language model is trained to handle errors in the household appliance.
- the error handling can include errors reported by the household appliance itself or errors noticed by the user due to a faulty function.
- Function or repair documentation or forum conversations can also be used as training material for this.
- the language model's achievable answers can improve in quality if the additional training data mentioned is as precise and as comprehensive as possible.
- An operator of a language model can offer an interface via which special knowledge can be contributed or made accessible to the language model.
- training data relating to the household appliance can be combined modularly with general training data of the language model.
- the training data provided can be separable from the rest of the language model complex so that mixing or combining only takes place under predetermined conditions. For example, it can be ensured that the language model only accesses the additional information if a specific interface provided by the operator is used.
- a user who uses a different, in particular a public, interface of the language model can receive answers that are not based on the specifically contributed training data.
- a predetermined keyword or key phrase is first recognized, which precedes the assistance request. This means that it can first only be checked whether the keyword can be recognized in acoustic data in the area of the household appliance, and only if this is the case can further processing of audio data can be started. The privacy of a person in the area of the household appliance can thus be better protected. In addition, analysis of verbal utterances that do not include a request for support can be prevented.
- the linguistically formulated support request is converted into a textual representation using a predetermined vocabulary that is related in particular to the household appliance.
- a recognition model for converting spoken language can be trained in addition to recognizing technical terms and proper names in connection with the household appliance.
- a modular approach in which the trained technical terms can be separated from a general vocabulary can be supported. The approach for this can correspond to that regarding the modularity of learning content in the language model.
- a device for controlling a household appliance comprises at least one microphone in the area of the household appliance for detecting a verbally formulated support request; an acoustic output device in the area of the household appliance; a communication device for communicating with a service external to the household appliance; and a processing device.
- the processing device is configured to transmit an indication of the support request to the external service; to receive a response to the support request; and to output a linguistic representation of the response.
- the device and in particular the processing device it comprises are preferably designed to at least partially carry out a method described herein.
- the method can be in the form of a computer program product with program code means.
- the computer program product can be stored on a computer-readable data carrier. Additional features or advantages of the method can be transferred to the device or vice versa.
- the device can be retrofitted cost-effectively to a household appliance if it already contains one or more of the components mentioned.
- the communication device is preferably designed to provide a wired or wireless connection to the external service via a data or communication network.
- the communication device can be designed to communicate with a mobile network or the Internet.
- the device further includes a device for detecting a predetermined keyword that precedes the support request.
- the processing device is designed to forward the reference to the support request to the external service only after recognizing the keyword.
- the conversion of the support request from an acoustic to a textual form can also be carried out by the device.
- the device comprises a device for converting the support request into a textual representation; the indication comprises the textual representation.
- the conversion can be carried out by an external service that is contacted via the communication device. The external service can be implemented separately from the language model or combined with it.
- the response is received in text form, the device further comprising a device for converting the response into a linguistic representation.
- the response in text form can thus only be small in scope and can be transmitted quickly to the household appliance. Conversion into a linguistic representation then only takes place in the household appliance.
- an interface is provided for controlling a function of the household appliance depending on the answer.
- an optical display device can be used to output the answer in text form.
- an optical indication of a control element of the household appliance to be used can be highlighted in accordance with the answer.
- a household appliance comprises a device described herein.
- the household appliance can be intended in particular for laundry care and can comprise a washing machine or a dryer.
- Other exemplary household appliances that can be used with the device can be equipped with an extractor hood or a coffee machine.
- a system for controlling a household appliance comprises at least one microphone in the area of the household appliance for detecting a linguistically formulated support request; a device for determining a textual representation of the support request; a language model that is configured to provide a response in text form to a textually represented support request; a device for providing a linguistic representation of a response represented in text form; and an acoustic output device in the area of the household appliance for acoustically outputting a provided linguistic representation.
- the system can in particular comprise a household appliance described herein and a service that is external to the household appliance. Further services can implement additional functionalities. It is preferred that the system is set up for use by a large number of household appliances.
- the household appliances can, for example, belong to a common appliance class or be manufactured by the same manufacturer.
- Figure 1 a system
- Figure 2 shows a flow chart of a method.
- FIG. 1 shows a system 100 for controlling a household appliance 105.
- the household appliance 105 is designed to serve a predetermined purpose in a household. This purpose can include, in particular, laundry care or a task in a kitchen.
- a user 110 can use the household appliance 105.
- the male gender is used for the user 110 purely by way of example and without any specific intention or restriction.
- the household appliance 105 comprises a device 112 for controlling an interaction with the user 110.
- the device 112 comprises at least one microphone 115 which is attached to the household appliance 105 in such a way that it records spoken words in the area of the household appliance 105.
- the microphones 115 can be attached to the household appliance 105 in different areas or with different orientations.
- a pre-processing 120 is provided, which is designed to process and improve a detected acoustic signal. For example, noise suppression can be applied, a frequency response can be adjusted, background or interference noises can be suppressed, or a speaker can be isolated from a complex audio signal with multiple speakers.
- the pre-processing 120 can comprise a digital or analog signal processor.
- a keyword recognition 125 is set up to recognize an occurrence of a predetermined keyword in an audio data stream.
- the keyword is preferably selected such that it is conspicuous in terms of signal technology in a typical household audio data stream and a user 110 can easily remember it.
- a processing device 130 is designed to control at least one of the components of the household appliance 105 shown.
- the processing device 130 can provide audio data provided by the preprocessing 120 to an external service 140 by means of a communication device 135.
- a response from the external service 140 can also be received by means of the communication device 135 and provided acoustically to the user 110 by means of an output device 145 in the area of the household appliance 105.
- the output device 145 preferably comprises a loudspeaker and more preferably a matching amplifier.
- Acoustic data provided to the outside by the communication device 135 can be converted by a service 150.
- This is also referred to as speech-to-text (STT).
- the conversion of speech data into text form can also be carried out by means of a component 150 that is part of the household appliance 105 or the device 112. In this case, the component 150 is connected upstream of the communication device 135 in the direction of the external service 140.
- the provided text data which is a representation of the support request of the user 110, can be provided to a language model 155.
- the language model 155 is preferably a large language model that is trained to process general language texts using a large variety of data.
- additional training data 160 may be provided, in particular by a manufacturer of the household appliance 105, which may be combined or interwoven with the general data. It is preferred that the use of the additional training data 160 is limited to use cases in connection with the household appliance 105.
- the language model 155 can provide a response based on the support request, which is usually also in text form.
- the response can be converted by means of a component 165 into acoustic data that corresponds to a spoken word of the textual response.
- This technology is also called text-to-speech (TTS).
- TTS text-to-speech
- the component 165 is shown as a service outside of the household appliance 105.
- An output of the component 165 can be transmitted to the household appliance 105 by means of the communication device 135.
- a component 165 with the same functionality can also be included in the household appliance 105 or the device 112, so that the text data of the language model 155 first passes through the communication device 135 and only then reaches the component 165.
- the acoustic data provided in this way can be output to the user by means of the acoustic output device 145 in the area of the household appliance 105.
- the processing device 130 can provide part of the data to the user 110 by means of a device of the household appliance 105.
- information can be exchanged via an interface 170.
- an output device in the form of a text display can be provided, and the response can be provided not only in acoustic but also in text form on the household appliance 105.
- the user 110 makes a linguistic support request to the household appliance 105, his spoken words can be converted into text, converted into a response using the language model 155, and the response can be output to the user 110 on the household appliance 105. This can give the user 110 the impression that the household appliance 105 is capable of dialogue.
- an assistance request may include advice on operating the household appliance 105 to achieve a predetermined goal.
- the household appliance 105 comprises a washing machine
- the user 110 can request assistance with a cleaning or operating problem as follows:
- the first part of this statement may correspond to the predetermined keyword to cause processing of the following sentence.
- An exemplary response provided to the user 110 by the language model 155 to this sentence could be:
- the user 110 can also seek advice if a problem occurs with the household appliance 105.
- the user can ask a question related to a general operation of the household appliance 105:
- this response could then be output as voice data on the household appliance 105:
- the washing machine is still in the middle of a wash cycle. Make sure that the washing machine has finished its cycle and the 'door locked' indicator light has gone out.”
- additional information that depicts a device status of the household appliance 105 can also be taken into account.
- the device status can be transmitted together with the request to the language model 155.
- the device status is also available in text form so that it can be read by a human.
- the user 110 can ask a question regarding operation or maintenance of the household appliance 105:
- the user 110 may inquire about the meaning of an existing error or an error code that the household appliance 105 is issuing:
- a device status of the household appliance 105 here for example the error code provided, can be transmitted and provided together with the linguistic request to the language model 155.
- a possible answer could be:
- FIG. 2 shows a flow chart of an exemplary method 200 for controlling a household appliance 105.
- the method 200 preferably begins in a step 205, in which the pronunciation of a predetermined keyword is detected in the area of the household appliance 105.
- a linguistic request following the keyword to assist in handling the household appliance 105 can be detected.
- the recorded request can be converted into text form in a step 215.
- the STT component 150 in the household appliance 105 or an STT service 150 outside the appliance 105 can be used for this purpose. Speech recognition can be based on machine learning, for example using an artificial neural network trained for this purpose. Available STT components can support different speakers and/or different languages or dialects.
- a special vocabulary can be used that is related to the household appliance 105 in question or the task to be performed with it.
- the special vocabulary can be entered into the STT component for general recognition or used modularly only for requests in the present context. It is preferred that a manufacturer of the household appliance 105 provides information about an expected vocabulary to a provider of the STT component.
- the support request in text form can be fed to the language model 155 in a step 220.
- additional information can also be provided to the language model 155, which in particular relates to an identification, a device type, a device model and/or a status of the household appliance 105.
- This information is preferably also expressed in text form.
- a status of the household appliance 105 can include a number of structured parameters that can be expressed in an XML structure or in JSON format, for example.
- the language model 155 determines a response in text form with regard to the support request in text form and, if applicable, the further information on the basis of the training data made available to it.
- the response can be converted into a linguistic representation.
- a TTS service 165 outside the household appliance 105 can be used, or a TTS component 165 is included in the household appliance 105 for this purpose.
- the specific linguistic representation can be output in the area of the household appliance 105 so that the user 110 can hear it.
- the dialogue with the language model 155 - or the perceived dialogue with the household appliance 105 - can be continued by running through the method 200 again.
- the method 200 can be run through as often as necessary to enable the user 110 to enable the user to use his household appliance 105 in the planned manner or in the best possible way.
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- Engineering & Computer Science (AREA)
- Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- Audiology, Speech & Language Pathology (AREA)
- Human Computer Interaction (AREA)
- Multimedia (AREA)
- Computational Linguistics (AREA)
- Acoustics & Sound (AREA)
- Theoretical Computer Science (AREA)
- Artificial Intelligence (AREA)
- General Health & Medical Sciences (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Selective Calling Equipment (AREA)
Abstract
Description
Claims
Priority Applications (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202480039571.8A CN121336255A (zh) | 2023-06-13 | 2024-06-10 | 家用电器的控制 |
| EP24732289.4A EP4728506A1 (de) | 2023-06-13 | 2024-06-10 | Steuern eines haushaltsgeräts |
Applications Claiming Priority (2)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| DE102023205462.0A DE102023205462A1 (de) | 2023-06-13 | 2023-06-13 | Steuern eines Haushaltsgeräts |
| DE102023205462.0 | 2023-06-13 |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| WO2024256344A1 true WO2024256344A1 (de) | 2024-12-19 |
Family
ID=91469886
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| PCT/EP2024/065965 Ceased WO2024256344A1 (de) | 2023-06-13 | 2024-06-10 | Steuern eines haushaltsgeräts |
Country Status (4)
| Country | Link |
|---|---|
| EP (1) | EP4728506A1 (de) |
| CN (1) | CN121336255A (de) |
| DE (1) | DE102023205462A1 (de) |
| WO (1) | WO2024256344A1 (de) |
Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20210097990A1 (en) * | 2019-10-01 | 2021-04-01 | Lg Electronics Inc. | Speech processing method and apparatus therefor |
Family Cites Families (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US6513006B2 (en) * | 1999-08-26 | 2003-01-28 | Matsushita Electronic Industrial Co., Ltd. | Automatic control of household activity using speech recognition and natural language |
| CN112840256A (zh) * | 2018-10-15 | 2021-05-25 | 住友电气工业株式会社 | 光模块及光模块的制造方法 |
-
2023
- 2023-06-13 DE DE102023205462.0A patent/DE102023205462A1/de active Pending
-
2024
- 2024-06-10 WO PCT/EP2024/065965 patent/WO2024256344A1/de not_active Ceased
- 2024-06-10 EP EP24732289.4A patent/EP4728506A1/de active Pending
- 2024-06-10 CN CN202480039571.8A patent/CN121336255A/zh active Pending
Patent Citations (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20210097990A1 (en) * | 2019-10-01 | 2021-04-01 | Lg Electronics Inc. | Speech processing method and apparatus therefor |
Non-Patent Citations (1)
| Title |
|---|
| EVAN KING ET AL: "Sasha: creative goal-oriented reasoning in smart homes with large language models", ARXIV.ORG, CORNELL UNIVERSITY LIBRARY, 201 OLIN LIBRARY CORNELL UNIVERSITY ITHACA, NY 14853, 16 May 2023 (2023-05-16), XP091510750 * |
Also Published As
| Publication number | Publication date |
|---|---|
| CN121336255A (zh) | 2026-01-13 |
| EP4728506A1 (de) | 2026-04-22 |
| DE102023205462A1 (de) | 2024-12-19 |
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